Improvement of weight computational statistical modeling via the transition to a subcritical Galton-Watson process
The widely used exponential transformation method in the Monte Carlo estimation is based on a modification of the exponential distribution of the particle's path with an auxiliary weight multiplied by a factor. The authors simplify this complex weighted algorithm by modifying the branching of the particle trajectory. In this way, they derive an expression for the second moment of the total number of particles in a subcritical Galton-Watson process.
scientific article; zbMATH DE number 6106385